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Unlearning’s Blind Spots: Over‑Unlearning and Prototypical Relearning Attack

Machine unlearning (MU) aims to expunge a designated forget set from a trained model without costly retraining, yet the existing techniques overlook two critical blind spots: “over‑unlearning" that deteriorates retained data near the forget set, and post‑hoc “relearning” attacks that aim to resurrec…